Project Summary_Abstract of Scale-Up Core We propose to evaluate a new mental health service delivery model in Latin America in which we plan to: (1) harness mobile behavioral health technology for mental health (with a primary focus on depression), (2) launch new workforce training and service delivery models (including the integration of technology into service delivery), (3) launch and evolve an integrated data management system for systematic data tracking and outcomes assessment, and (4) launch and grow a learning collaborative of organizations integrating mental health into primary care. We will launch this project at multiple primary care sites in various parts of Colombia, with a plan to inform subsequent adoption in several other Latin American countries, including Chile and Peru. To accomplish our planned implementation research Aim within the Scale-Up Study Core, we will (1) conduct formative work (e.g., key informant interviews, observational studies) with multiple stakeholders (patients, clinicians, healthcare systems, payers, policymakers) to inform and refine the planned mental health service delivery model (Year One), (2) pilot test this service delivery model at a single site (early in Year Two), and (3) refine the model based on pilot data and expand implementation across multiple Colombia-based healthcare sites in urban and rural communities on a staggered basis (Years Two-Five). Importantly, we will track outcomes (described below) at ?control? sites at each of our partnering primary care program, consisting of comparable primary care programs that do not implement the novel mental health service delivery model. We will evaluate (Years Two-Five) the ability of our proposed approach to accelerate the translation of evidence-based mental health services into practice and expand research capacity at multiple levels. We will measure implementation outcomes, including: (1) the ability of this model to accelerate the adoption of science-based mental health service delivery (e.g., its ability to increase capacity to provide evidence-based resources to more individuals), (2) the acceptability of the model for healthcare service delivery (e.g., increase patient engagement in their own self-management), and (3) the model's impact on costs of care (e.g., to decrease costs per beneficiary). We will also collect patient level data outcomes as a secondary focus to assess (4) the model's impact on public/population health (e.g., its effects on improving behavioral health and health outcomes). We will also measure implementation context measures to evaluate barriers and facilitators to implementation related to: intervention characteristics, organization characteristics (e.g., climate, readiness), individual characteristics (i.e., provider/staff attitudes; patient attitudes and experiences), and external influences (e.g., socio-political characteristics local technology infrastructure i.e., wireless in the community, state policy/regulations, and reimbursement models). We will additionally conduct exploratory moderator and mediator analyses to examine how implementation context variables relate to implementation outcomes.